In recent years, there have been a wave of articles professing that digital transformation is about people, not technology. The argument typically runs along the lines that it takes people to execute the strategy and without the right skills, culture and change management, any digital transformation initiative will likely miss the mark. While this is accurate, the same could be said of most major initiatives.

The real requirements for success in digital transformation involve both people and technology. Without technology, digital transformation is just transformation, and the benefits of making digital an integral part of the business strategy are lost. Ideally the business strategy and the digital strategy should be “one and the same” so the business can fully capitalize on the opportunities afforded by digital.

We’ve all heard of the sharing economy and the gig economy, but a new business model is quietly introducing itself across many consumer-facing industries. It’s an extreme form of the convenience economy that I like to term the “lazy economy.” The term is somewhat tongue-in-cheek, but there’s some real implications in these nascent business models for CIOs.

As you might expect, the lazy economy is characterized by hyper-convenient products and services that go the extra mile for the customer. To point, in fact, where subscribing to these services as a consumer may trigger surprise from more proactive, do-it-yourself (DIY)-oriented friends. A few examples include the drone that delivers coffee to you when it detects you’re looking tired (patent stage), food delivered into your fridge while you’re out, robotic mowers that cut your garden, and gas refueling services that deliver fuel directly to your car. You could add dog walking services to the list as well.

In recent years, as each new emerging technology or trend has appeared, we’ve seen widespread calls by tech and industry pundits for organizations to create new CXO positions specifically for each technology or trend.

While it’s tempting to create these new positions to get to grips with the business implications of the technology or trend in question, and to take advantage of the opportunities presented, if you were to act on all this advice you’d likely have over 20 new CXOs reporting directly into the CEO or tiered in elsewhere across the C-suite.

As with other disruptive technologies such as augmented/virtual reality, blockchain, drones/UAVs and the Internet of Things, artificial intelligence (AI) has significant potential to transform business models, processes, products and services. According to McKinsey, it’s estimated that AI has the potential to deliver additional global economic activity of around $13 trillion by 2030, or about 16 percent higher cumulative GDP compared with today. This amounts to 1.2 percent additional GDP growth per year.

While many companies are well into their digital transformation journey, it’s been widely reported that relatively few organizations are truly thriving or succeeding. Consultancy Inc.Digital, for example, cites only 18% of organizations as digitally thriving and consultancy ClearPrism has found that “fewer than 12% of companies capture more than 85% of economic profit in any industry.”

Difficulties in execution aside, digital transformation is clearly an ongoing journey, not a destination, but how many organizations have a truly clear picture of where they want to go? What’s the end game for their transformation? Is it customer obsession, revenue growth, cost reduction, process improvement, greater competitive differentiation, accelerated innovation, increased market share, improved shareholder value, all of the above, or perhaps something more?

According to Goldman Sachs, the drone market is projected to be a $100 billion opportunity between 2016 and 2020. Key markets include military ($70 billion), consumer ($17 billion), and commercial/civil ($13 billion) with the latter being the fastest growth opportunity.

“Design thinking is a creative problem-solving — and opportunity-finding — mindset and methodology with a bias toward action that puts the emphasis on empathizing with the customer, clearly defining the problem, collaboratively ideating solutions, and then prototyping and testing those solutions.”

Design thinking is an overall approach that puts the focus on the customer and covers a full range of disciplines and process steps across empathy, definition, ideation, prototyping and testing. As you think about how to infuse the design thinking mindset into your corporate innovation program, it can be useful to develop a set of design thinking considerations specifically for this middle-discipline of ideation.

Walmart and Microsoft recently announced a five-year strategic partnership to further accelerate digital innovation in retail. This comes as a major announcement both for observers of the cloud wars as well as observers of the continuing digital transformation in retail. The agreement will leverage a broad base of Microsoft’s cloud, AI and IoT solutions for Walmart’s enterprise-wide use – including a wide range of external customer-facing services and internal business applications.

With the rapid pace of innovation continually disrupting business models, and in many cases entire industries, how will online learning keep up to provide the relevant courseware for today’s and tomorrow’s workforce? This will be essential for economic growth and to support a thriving, college-educated workforce that’s equipped with the very latest knowledge, ideas and technology.

In the future, I believe that institutions at the forefront of online education will be recognized via several capabilities which will have digitally transformed today’s EdTech market. They will include a powerful combination of omni-channel learning pathways, cognitive courseware, virtual counselors and AI-enabled course development and grading.

If you’re a regular reader of my column, you’ll know that I write a lot about best practices in corporate innovation and associated strategic themes, techniques and approaches for establishing world-class programs.

While we can learn a lot from studying best practices, it’s also helpful – at least once in a while – to study what we might consider worst practices and what not to do as a way to avoid some of classic pitfalls for both aspiring and as well as already highly-successful innovators.

Here are four warning signs I believe are important for organizations to be aware of and to have a strategy to counter even if you consider your company to be a world-class innovator:

For most tech-company CEOs and entrepreneurs, having a platform business model and successfully taking it to scale is stuff of legend. Due to their network effects and ability to create a virtuous cycle where the benefit of a product or service increases as more people use it, platform business models have become the dominant business model for the digital economy.

Platforms have proven themselves in the high tech and B2C space with household names such as Apple, Airbnb, Microsoft and Uber and in recent years have become the go-to strategy for B2B industry clouds such as those of GE Predix, Philips HealthSuite and many others.

While AI’s impact on the workforce is clearly top-of-mind for most organizations, executives have many additional questions which need to be addressed to clarify the impact of the technology on their business models, processes, products and services – and their market and competitive position under different AI adoption scenarios.

The exact question set varies by executive role. While the CEO is mostly interested in implications on corporate growth, competitive position and differentiation, the CFO may be interested in how much it will reshape the workforce, and the CIO may be interested in which existing business applications and processes may be impacted the most – as well as when and where to make strategic AI investments.

Leaders in public sector organizations are facing ever-increasing demands and expectations from their constituents to deliver services more effectively and efficiently, to streamline processes, improve productivity, reduce costs, and improve customer satisfaction all the while dealing with limited resources in terms of personnel and budgets.

In this environment, innovation – and, more specifically, accelerating the pace of innovation – is both a necessity and a challenge in terms of keeping up with the pace of commercial innovation and applying it swiftly to modernize and transform existing systems and processes. With this in mind, here’s five ways public sector leaders can accelerate their innovation initiatives in 2018:

With so much interest and activity around innovation workshops, design thinking workshops and other forms of event-based idea generation (ideation) sessions in support of digital transformation initiatives, it’s time to re-visit the age-old Post-It’s versus software debate.

Of course, a well-run ideation session using Post-It’s will trump a less-effectively run session using software every time, so it’s more about the magician (in this case the facilitator) and the overall process, including the participant experience and engagement level, than his or her specific tools.

Some of the key items to consider before you think about technology include setting appropriate goals and objectives, engaging the right participants to support these objectives, giving participants sufficient upfront context setting prior to brainstorming, and keeping them engaged throughout the session.

Last year, my predictions for digital transformation were focused on the core DNA that organizations needed to put into place to achieve world-leading performance and results in digital transformation.

In addition to perennial themes such as leadership, people and cultural competencies, these new strategic themes for digital transformation included disruptive technologies, platform business models, digital services mastery and leading practices in corporate innovation.

Rather than focusing on discrete technologies, the themes were designed to help organizations focus on the bigger picture to advance their digital strategies, their overall digital transformation maturity, and their corresponding industry competitiveness and agility.

The Royal National Lifeboat Institution (RNLI) is a UK-based charity whose mission is to save lives at sea. The charity was founded back in 1824 and their lifeboat crews and lifeguards have saved over 140,000 lives to date. You might think that digital technologies lend little value to aid in at-sea rescues, but on closer inspection it is energizing RNLI’s goal to cut lives lost due to drowning by 50% by 2024.

There are over 350 lifeboats in the RNLI fleet based at various stations around the UK and Ireland. Between them, RNLI lifeboats cover 19,000 miles of coastline and some busy inland stretches of water using all-weather lifeboats as well as inshore lifeboats and even hovercraft. The different classes of lifeboat in their fleet mean they can reach people in all kinds of situations and locations.

Platform business models allow enterprises to set up powerful industry-focused, cloud-based ecosystems for value exchange and innovation among participants. After their initial debut in the tech sector, they’re now appearing across almost all industry verticals, including finance, healthcare, manufacturing, public sector, telecom, transportation and utilities.

With many organizations now three to five years into their digital transformation strategies, the role of the Chief Digital Officer (CDO) has been rapidly evolving and maturing alongside. What started as a role close to that of the Chief Marketing Officer, with a focus on the digital customer experience, has now evolved into something far-more expansive – reaching into corporate strategy, innovation, technology and operations.

In this article, we’ll look at how the CDO role started, some of the latest developments in its continued evolution, the different types of capabilities that are needed to achieve transformational results, and some recommendations for organizations wishing to lead, rather than follow, in terms of digital disruption within their industries.

With bitcoin crossing the $4K mark and the market cap for cryptocurrencies currently residing around $140B, there’s a definite sense of a gold rush in progress much like the dot-com era and the real California gold rush of the 1800s.

While parallels with the dot-com era have been well reported, especially related to exploring what phase of the bubble we’re in, there’s been relatively less comparison with the California gold rush. So what can history teach us from the physical gold rush that may guide us in the midst of today’s digital equivalent? To help address this question, here’s some parallels between the two and some recommendations for organizations in terms of charting your course.

With most organizations now several years into their digital transformation journeys, many are looking to measure progress, gauge maturity, and benchmark against peers in their industry. The key questions are how to assess this maturity, what are the key pillars and elements of maturity, and which capabilities are new and different compared to business as usual.

Digital transformation is a broad subject that requires competency across strategy and vision, people and culture, process and governance, and technology and capabilities, as show in following chart:

With most organizations now several years into their digital transformation journeys, many are looking to measure progress, gauge maturity, and benchmark against peers in their industry. The key questions are how to assess this maturity, what are the key pillars and elements of maturity, and which capabilities are new and different compared to business as usual.

Digital transformation is a broad subject that requires competency across strategy and vision, people and culture, process and governance, and technology and capabilities, as shown in the figure below.

If you're leading a corporate innovation program for your organization, or you're part of the core innovation team, one of the key considerations after it's been up and running for a while is how to continuously improve and refine the program over time.

While there's a lot of attention paid to how to design and implement corporate innovation programs, as well as how to run ongoing and event-based ideation (i.e., idea generation) sessions with various constituencies, there's not so much written about how to effectively operate these programs and capabilities on a sustainable, year-over-year basis.

A corporate innovation program clearly needs to evolve and adapt over time to incorporate the latest developments in innovation management theory and practice, and to fine-tune the sights around innovation as customer needs, business needs and overall market conditions dictate.

In recent years, we've started to see terms such as "innovation antibodies" and "innovation theater" being used to describe some of the challenges in managing innovation, particularly in larger organizations trying to find their own innovation culture. Today, many innovation leaders must carefully navigate the waters between too much resistance to innovation from corporate antibodies and, conversely, too much enthusiasm for innovation from those wishing to put on theater.

So-called "innovation antibodies" are well-known for their ability to stifle ideas or even kill off ideas completely. The antibodies are typically corporate departments and personnel that see new ideas coming from another part of the business as risk elements that need to be carefully managed and mitigated. Harvard Business Review published a useful article a few years ago about how to get the corporate antibodies on your side by making these departments and staff part of the solution.

And in the spirit of "making IT good for society" (in the words of the British Computer Society), there's a tremendous opportunity for the technology community to make a difference. The scope of this opportunity now extends well beyond green IT to focus on using digital transformation to help all industries meet their sustainability goals and reduce their carbon footprints.

While the concepts of green IT and sustainable IT were originally focused on IT operations and the technology product lifecycle, the new call to action as companies undergo digital reinvention is for them to give environmental factors early consideration in their planning and to extend the scope of their sustainability improvements beyond IT operations and across many of their digitally transformed processes.

When we think of digital disruption, while all industries are affected in one way or another, some of the largest disruptions ahead may well be experienced within financial services. Of course, bitcoin and blockchain come to mind right away, as well as A.I. for improved customer service and a competitive edge, but there are numerous other disruptions either already in play or poised to take effect very soon.

While discrete technology trends often get all the attention in New Year's lists, this coming year will be highlighted by organizations taking a more holistic focus on digital transformation that taps into platform business models, the power of technology combinations, mastery of digital services and leading practices in corporate innovation. There will also be an increasing number of "world-firsts" coming out from the corporate sector as vertical industries refine their mastery of digital business.

In light of those impending developments, here are five digital business predictions for 2017 that C-levels need to consider when planning for the year ahead.

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IT LeadershipDigital TransformationInnovationEmerging TechnologyIDG Contributor Network: Platform business models: A primerWed, 26 Oct 2016 12:09:00 -0700Nicholas D. EvansNicholas D. EvansPlatform business models are gaining a lot of attention lately, but not everyone knows precisely what they are. These business models, which allow enterprises to set up powerful ecosystems for value exchange and innovation among participants, can be used across industries and are fast becoming a dominant business model for the digital economy.

If you're involved in managing innovation for your organization, you're likely working with some form of enterprise innovation management software, or you're in the process of selecting a solution that can best support your needs.

To help you think about future needs with regard to managing innovation, I have identified five areas where I believe today's innovation management software needs to evolve to support the ever-expanding needs of the business with regard to digital transformation.

Professor Sanjay Sarma is best known for his ground-breaking work in co-founding the MIT Auto-ID Center, the predecessor of today’s MIT Auto-ID Labs, and developing many of the key technologies behind the EPC suite of RFID standards now used worldwide. He was also the founder and CTO of OATSystems, which was acquired by Checkpoint Systems in 2008.

The Auto-ID Center was first created, it was chartered with creating the infrastructure, recommending the standards and identifying the automated identification applications for a networked physical world. It was during this period back in 1999 that the term “Internet of Things” was coined and “things” truly started to get connected to the Internet.

Even if you’re working in an industry outside of the financial services sector, it’s more than likely you’ve come across blockchain, the cryptographic technology that underlies bitcoin, and you’re exploring its strategic significance for your business.

According to The Economist, “blockchain has applications well beyond cash and currency. It offers a way for people who do not know or trust each other to create a record of who owns what that will compel the assent of everyone concerned. It is a way of making and preserving truths.”